Method and apparatus for optically imaging solid tumor tissue

ABSTRACT

The present invention provides a method for determining the presence of solid tumor tissue, for identifying and mapping the margins of solid tumors during surgical or diagnostic procedures, and for grading and characterizing tumor tissue by detecting changes in the optical properties of an area of interest suspected to contain tumor tissue.

CROSS REFERENCE TO RELATED APPLICATIONS

This patent application is a continuation of application Ser. No.08/477,468, filed Jun. 7, 1995, issued Dec. 23, 1997 as U.S. Pat. No.5,699,798, which is a continuation-in-part of U.S. patent applicationSer. No. 08/073,353, filed Jun. 7, 1993 and issued as U.S. Pat. No.5,465,718, which is a continuation-in-part of U.S. patent applicationSer. No. 07/894,270, filed on Jun. 8, 1992 and issued as U.S. Pat. No.5,438,989, which is a continuation-in-part of U.S. patent applicationSer. No. 07/565,454 filed on Aug. 10, 1990 and issued as U.S. Pat. No.5,215,095, all of which are incorporated herein by reference in theirentirety.

TECHNICAL FIELD OF THE INVENTION

The present invention relates to methods and apparatus for opticallyimaging tumor tissue. More specifically, the methods and apparatus ofthe present invention may be used to distinguish tumor tissue fromnormal tissue and to grade and characterize tumor tissue.

BACKGROUND OF THE INVENTION

A primary goal of surgical treatment of tumors is the complete removalof abnormal or pathological tissue while sparing normal areas. Hence, asurgeon attempts to distinguish abnormal tissue from adjacent areas ofnormal tissue and to identify boundaries of pathological tissue so thatpathological tissue may be removed without affecting surrounding areas.For example, when removing tumors from the cortex, it is important thatsubstantially all the pathological tissue be removed while minimizingdamage to cortical tissue committed to important functions, such aslanguage, motor and sensory areas.

Incidence rates for primary intracranial brain tumors are in the rangeof 50-150 cases per million population or about 18,000 cases per year.Approximately one half of brain tumors are malignant. Malignant braintumors in adults occur predominantly in the age range of 40-55 yearswhile the incidence of more benign tumors peaks near 35 years of age. Aprimary means for treatment of such tumors is surgical removal. Manystudies have shown that clinical outcome is improved when more of thetotal amount of tumor tissue is removed. For gross total resections oftumors, the 5-year survival rate is doubled when compared to subtotalresection. Both duration of survival and independent status of thepatient are prolonged when the extent of resection is maximized inmalignant gliomas. Current intraoperative techniques do not providerapid differentiation of tumor tissue from normal brain tissue,especially once the resection of the tumor begins. Development oftechniques that enhance the ability to identify tumor tissueintraoperatively may result in maximizing the degree of tumor resection,thereby prolonging survival.

Of the 500,000 patients projected to die of systemic cancer per year inthe United States, approximately 25%, or over 125,000, can be expectedto have intracranial metastasis. The primary focus for surgery in thisgroup is those patients with single lesions who do not have widespreador progressive cancer. This group represents about 20-25% of patientswith metastases (30,000), however, the actual number of patients thatare good candidates for surgery is slightly smaller. Currently, of thosepatients undergoing surgery, one half will have local recurrence oftheir tumor at the site of operation, while the other half will developa tumor elsewhere. The fact that about 50% of the surgeries fail at thesite of operation means that an improved ability to remove as much tumoras possible by detecting and localizing tumor margins during tumorremoval could potentially decrease the incidence of local recurrence.

Thus, for both primary and metastatic tumors, the more tumor tissueremoved, the better the outcome and the longer the survival. Further, bymaximizing the extent of resection, the length of functional, goodquality survival is also increased.

Most current tumor imaging techniques are performed before surgery toprovide information about tumor location. Presurgery imaging methodsinclude magnetic resonance imaging (MRI) and computerized tomography(CT). In the operating room, only intraoperative ultrasound andstereotaxic systems can provide information about the location oftumors. Ultrasound shows location of the tumor from the surface, but,once surgery begins, does not provide information to the surgeonnecessary to prevent destruction of important functional tissue whilepermitting maximal removal of tumor tissue. Stereotaxic systems coupledwith advanced imaging techniques have (at select few hospitals) beenable to localize tumor margins based upon the preoperative CT or MRIscans. However, studies have shown that the actual tumor extends 2-3 cmbeyond where the image enhanced putative tumor is located onpreoperative images. Therefore, the only reliable method currentlyavailable for determining the location of tumors is to obtain multiplebiopsies during surgery and wait for results of microscopic examinationof frozen sections. This technique, known as multiple histologicalmargin sampling, suffers several drawbacks. First, this is atime-consuming procedure and can add about 30 to 90 minutes (dependingupon the number of samples taken) to the length of time the patient isunder anesthesia. The increased time required for margin sampling leadsto increased medical costs, as operating room time costs are high.Moreover, increased operating room time for the patient increases theprobability of infection. Multiple histological margin sampling is proneto errors, as the pathologist must prepare and evaluate samples in shortorder. In addition, margin sampling does not truly evaluate all regionssurrounding a primary tumor and some areas of residual tumor can bemissed due to sampling error. Thus, although patient outcome isdependent upon aggressive removal of tumor tissue, a surgeon must oftenrely upon an estimation technique as a guide. Surgeons must makedifficult decisions between aggressively removing tissue and destroyingsurrounding functional tissue, and may not know the true outcome of theprocedure until permanent tissue sections are available about one weeklater. Consequently, an additional surgical procedure may be required.

Other techniques developed to improve imaging of solid tumor massesduring surgery include determining the shape of visible luminescencespectra from normal and cancerous tissue. U.S. Pat. No. 4,930,516teaches that the shape of visible luminescence spectra from normal andcancerous tissue are different. Specifically, there is a shift to bluewith different luminescent intensity peaks in cancerous tissue ascompared to normal tissue. Thus it is possible to distinguish canceroustissue by exciting the tissue with a beam of ultraviolet (UV) light andcomparing visible native luminescence emitted from the tissue withluminescence from a non-cancerous control of the same tissue type. Sucha procedure is fraught with difficulties since a real time, spatial mapof the tumor location is not provided for the use of a surgeon.Moreover, the use of UV light as an excitation wavelength can causephotodynamic changes to normal cells and is dangerous for use in anoperating room. In addition, UV light penetrates only superficially intotissue and requires quartz optical components instead of glass.

Optical imaging of tissue using techniques and apparatus similar tothose described herein is described in U.S. Pat. Nos. 5,699,798,5,465,718 and 5,419,989, all of which are incorporated herein byreference in their entirety.

Therefore, there remains a need in the art for a more effective methodand device for determining solid tumor locations and precisely mappingtumor margins in a real-time mode during surgery. Such a method anddevice should further be useful for inexpensive evaluation of any solidtumor by a non-invasive procedure (e.g., breast mammography) and becapable of grading and characterizing tumors.

SUMMARY OF THE INVENTION

The methods and device described herein can be used to opticallydistinguish between tumor and non-tumor tissue, and to image margins anddimensions of solid tumors during surgical or diagnostic procedures. Inaddition, the methods and device of the present invention can be used tograde and characterize solid tumor tissue, thereby distinguishingmalignant from non-malignant tumor tissue. For example, optical imagingtechniques of the present invention can be used by a surgeonintraoperatively to distinguish between tumor and non-tumor tissue witha high degree of spatial resolution. Although the optical imagingtechniques disclosed herein are used principally for in vivoapplications, they may also be used to distinguish between tumor andnon-tumor tissue in in vitro preparations. The optical imagingtechniques can be used to provide information in “real-time” andtherefore can be employed intraoperatively.

While the methods and apparatus of the present invention may be employedto optically image tumor tissue without the use of dyes orcontrast-enhancing agents, use of such agents provides images withhigher resolution and is therefore preferred. The dynamics of dyeperfusion through normal tissue differ from those through tumor tissue.Thus, using the methods and apparatus described herein, it is possibleto differentiate tumor tissue from surrounding normal tissue bymonitoring the changes in optical properties is resulting from thedifferent kinetics of dye uptake in tumor tissue compared to normaltissue.

Dyes suitable for use in the present invention include fluorescent andphosphorescent materials, dyes that bind to cell membranes, opticalprobes that preferentially accumulate in tumor tissue, phase resonancedye pairs, and the like. Examples of appropriate dyes includeindocyanines, fluoresceins, hematoporphyrins, and fluoresdamines. Apreferred dye is indocyanine green which has a broad absorptionwavelength range and a peak absorption in the range of 730 nm to 840 nm.Detectors appropriate for use with such dyes, or contrast enhancingagents, are well known in the art.

The apparatus of the present invention employs an electromagneticradiation (emr) source for uniformly illuminating an area of interest(i.e., an area believed to contain solid tumor tissue), and an opticaldetector capable of detecting and acquiring data relating to one or moreoptical properties of the area of interest. In a simple form, theapparatus of the present invention may include an optical fiber operablyconnected to an emr source that illuminates tissue, and another opticalfiber operably connected to an optical detector, such as a photodiode,that detects one or more optical properties of the illuminated tissue.The detector is used to obtain control data representing the “normal” or“background” optical properties of an area of interest, and to obtainsubsequent data representing the optical properties of an area ofinterest following administration of an image-enhancing dye, or during amonitoring interval. The subsequent data is compared to the control datato identify changes in optical properties representative of uptake ofdye by tumor tissue. According to a preferred embodiment, the control,subsequent and comparison data are presented in a visual format asimages.

Various types of optical detectors may be used, depending on the opticalproperty being detected, the format of data being collected, certainproperties of the area of interest, and the type of application, e.a.,intraoperative, diagnostic, monitoring, or the like. In general, anytype of photon detector may be utilized as an optical detector. Theoptical detector generally includes photon sensitive elements andoptical elements that enhance or process the detected optical signals.Numerous optical detectors are known and may be used or adapted for usein the methods and apparatus of the present invention.

Changes in optical properties that may be indicative of changes of dyeperfusion and therefore differentiate tumor from non-tumor tissueinclude, for example, reflection, refraction, diffraction, absorption,scattering, birefringence, refractive index, Kerr effect, and the like.The optical detection system may be incorporated in an apparatus for useexternal to the area of interest, or optical detection components may bemounted in an invasive or semi-invasive system, such as an endoscope,laparoscope or the like.

Numerous devices for acquiring, processing and displaying datarepresentative of one or more optical properties of an area of interestcan be employed. One preferred device is a video camera that acquirescontrol and subsequent images of an area of interest that can then becompared to identify areas of tumor tissue. Examination of imagesprovides precise spatial location of tumors and permits gradation andcharacterization of tumor tissue. Apparatus suitable for obtaining suchimages have been described in the patents incorporated herein byreference and are more fully described below. For most surgical anddiagnostic uses, the optical detector preferably provides images havinga high degree of spatial resolution at a magnification sufficient toprecisely locate the margins of a tumor. Several images are preferablyacquired over a predetermined time period and combined, such as byaveraging, to provide control and subsequent images for comparison.

Various data processing techniques may be advantageously used to assessthe data collected in accordance with the present invention. Comparisondata may be assessed or presented in a variety of formats. Processingmay include averaging or otherwise combining a plurality of data sets toproduce control, subsequent or comparison data sets. Images arepreferably converted from an analog to a digital form for processing,and back to an analog form for display.

Data processing may also include amplification of certain signals orportions of a data set (e.g., areas of an image) to enhance the contrastseen in data set comparisons, and to thereby identify areas of tumortissue with a high degree of spatial resolution. For example, accordingto one embodiment, images are processed using a transformation in whichimage pixel brightness values are remapped to cover a broader dynamicrange of values. A “low” value may be selected and mapped to zero, withall pixel brightness values at or below the low value set to zero, and a“high” value may be selected and mapped to a selected value, with allpixel brightness values at or above the high value mapped to the highvalue. Pixels having an intermediate brightness value, representing thedynamic changes in brightness indicative of changes in dye perfusion,may be mapped to linearly or logarithmically increasing brightnessvalues. This type of processing manipulation is frequently referred toas a “histogram stretch” and can be used according to the presentinvention to enhance the contrast of data sets, such as images,representing differences in tissue type.

Data processing techniques may also be used to manipulate data sets toprovide more accurate combined and comparison data. For example, patientmovement, respiration, heartbeat or reflex activity may shift an area ofinterest during detection of optical properties and data collection. Itis important that corresponding data points in data sets (such ascorresponding areas of an image) are precisely aligned to provideaccurate combined and comparison data. Such alignment may beaccomplished manually by a practitioner having specialized skill andexpertise, or using a variety of mathematical means. Optical markers maybe fixed at an area of interest and detected as the data is collected toaid in manual alignment or mathematical manipulation. Various processingtechniques are described below and in the patents incorporated herein byreference.

Inaccuracies and artifacts caused by patient movement during acquisitionof data can be reduced by mechanical means. According to a preferredembodiment, the emr source and the optical detector are provided as anintegral unit that is mountable to a patient during detection. Forexample, cranial posts may be used to mount an integrated emrsource/detector unit for localizing or mapping areas of cortical tumortissue. Likewise, an integrated unit including an emr source and anoptical detector may be mounted in a relatively “fixed” condition inproximity to other areas of interest.

Comparison data may be displayed in a variety of ways. For example,comparison data may be displayed in a graphical format that highlightsoptical differences indicative of tumor tissue. A preferred techniquefor presenting and displaying comparison data is in the form of visualimages or photographic frames corresponding to the area of interest.This format provides a visualizable spatial location (two- orthree-dimensional) of tumor tissue that is useful for treatment,diagnosis and monitoring. To enhance and provide better visualization ofcontrast between tumor and normal tissue, comparison images may beprocessed to provide an enhanced contrast grey scale or even a colorimage. A look up table (“LUT”) may be provided, for example, thatconverts the gray scale values for each pixel to a different (highercontrast) gray scale value, or to a color value. Color values may map toa range of grey scale values, or color may be used to distinguishbetween positive-going and negative-going optical changes. In general,color-converted images provide higher contrast images that highlightchanges in optical properties representing areas of tumor and normaltissue.

In operation, an area of interest in a patient is illuminated withelectromagnetic radiation (emr) while one or a series of data points ordata sets representing one or more optical properties of the area ofinterest is acquired. This data represents the control, or background,data. A series of data sets is preferably combined, for example byaveraging, to obtain a control data set. The control data set is storedfor comparison with data collected subsequently.

A subsequent data set representing the corresponding optical property isacquired during a subsequent time period following administration of adye by bolus injection into vasculature circulating to the area ofinterest. A series of subsequent data sets is preferably combined, forexample by averaging, to obtain a subsequent data set. The subsequentdata set is compared with the control data set to obtain a comparisondata set, preferably a difference data set. Comparison data sets canthen be examined for evidence of changes in optical propertiesrepresentative of areas of tumor versus non-tumor tissue within the areaof interest.

The methods and apparatus described herein may be employed to obtainthree-dimensional information of an area of interest suspected tocontain tumor tissue by: (a) illuminating the area of interest with aleast two different wavelengths of emr; (b) obtaining a sequence ofcontrol data sets corresponding to each wavelength of emr; (c)administering a dye; (d) obtaining a sequence of subsequent data setsfor each wavelength of emr; (e) obtaining a series of comparison datasets for each wavelength of light by subtracting the control data setfrom the subsequent data set or alternatively, in the case offluorescent dyes, subtracting the subsequent image from the controlimage; and (f) obtaining an enhanced comparison data set by ratioing thefirst comparison data set to the second comparison data set. Preferably,the area of interest is illuminated with monochromatic emr from a lasersource.

BRIEF DESCRIPTION OF THE DRAWINGS

The methods and apparatus of the present invention will be described ingreater detail below with reference to the following figures.

FIGS. 1A-1F illustrate identification of low grade human central nervoussystem (CNS) tumor tissue using the methods and apparatus of the presentinvention. This series of images is from a patient having a low gradeCNS tumor (astrocytoma, grade 1). Tumors of this type and grade arenotoriously difficult to distinguish from normal tissue once surgicalremoval of the tumor has begun. In FIG. 1A the lettered labels placedupon the brain by the surgeon overlay the tumor as identifiedintraoperatively by ultrasound. FIG. 1B shows a difference image takenapproximately 15 seconds after intravenous injection of dye (indocyaninegreen at 1 mg/kg). FIG. 1C shows the difference image about 30 secondsafter dye administration. The area of the tumor tissue showed the firsttissue staining. FIG. 1D shows that with this low grade tumor, alltissue (both normal and abnormal) showed staining at 45 sec after dyeadministration. FIG. 1E is an image of the area of interest one minuteafter dye administration and FIG. 1F is the image five minutes after dyeadministration, showing complete clearance in this low grade tumor.

FIGS. 2A-2E illustrate identification of a malignant human CNS tumorusing the methods and apparatus of the present invention. The series ofimages in this Figure are from the cortex of a patient with a malignantCNS tumor (glioblastoma; astrocytoma, Grade IV). FIG. 2A is a gray-scaleimage, taken before dye injection, showing that malignant brain tumortissue was densest in the center and to the right but that the tissueelsewhere was mostly normal. This was confirmed by pathology slides andflow cytometry data available one week after surgery. FIG. 2B is thedifference image at 15 seconds after intravenous injection ofindocyanine green, showing that the dynamics of dye perfusion in thefirst seconds in malignant tissue are similar to those in the first fewseconds in benign tumor tissue. FIG. 2C shows that at 30 seconds themalignant tissue is even more intense by comparison to the normaltissue. FIG. 2D (1 minute after dye injection) and 2E (10 minutes afterdye injection) show that dye is retained significantly longer inmalignant tissue than in benign tumor tissue, and in some cases,continues to sequester in the malignant tumor tissue over longer periodsof time.

FIGS. 3A-3D show identification of small remnants of tumor tissue in themargin of a resected malignant human CNS tumor using the presentinvention. The images are from an area of interest where a tumor wassurgically resected and biopsies were taken for multiple histologicalmargin sampling. The area of interest was thought to be free of tumortissue after the surgical removal of the tumor. Normally, in this sizeof a resection margin, only a single frozen sample would be taken forpathology analysis. For the purpose of this study, however, fivebiopsies were taken from the margin to aid in correlating the histologywith the optical image obtained by the present invention. FIG. 3A showsa gray-scale image of the tumor margin. FIG. 3B shows the margin withlabels that the surgeon placed directly on the brain. The purpose ofthese labels was to identify where the surgeon was going to removebiopsy samples for histological analysis after difference images wereacquired with the inventive device. FIG. 3C shows the difference image 1minute after intravenous injection of dye and FIG. 3D shows thedifference image 10 minutes after dye injection. These post-dyedifference images reveal a number of sites that contain tumor tissue aswell as areas of normal tissue. The accuracy of the optical imaging wasconfirmed post-operatively by analysis of the biopsies. Note that asmall area on the lower right of FIG. 3D indicates a possible region oftumor tissue that would not have been biopsied by the surgeon.

FIGS. 4D-4D illustrates use of the methods and apparatus of the presentinvention to identify and characterize tumors that do not contrastenhance with MRI imaging. Lack of contrast enhancement is usuallytypical of benign tumors, however a proportion of non-benign tumors arenot observable with current MRI imaging techniques. The images in thisFigure are from a patient whose tumor did not contrast enhance with MRI.However, optical imaging as described herein identified this tumor asnon-benign. Pathology and flow cytometry data, available one week later,confirmed that this tumor was an anaplastic astrocytoma. FIG. 4A showsthe gray-scale, field of view, image of the area of interest. FIG. 4Bshows the difference image, or control image, prior to dye injection.FIG. 4C shows the area of interest 1 minute after intravenous dyeinjection, and FIG. 4D shows the area of interest 5 minutes after dyeinjection. Note that the dye is retained in the tumor tissue for asignificant time. As shown in FIGS. 1A-1F, FIGS. 2A-2E and FIGS. 3A-3Dthis dynamic trait is characteristic of a non-benign tumor.

FIGS. 5A-5D show non-invasive imaging of dye dynamics and identificationof glioma through the intact cranium. FIG. 5A is a gray-scale image ofthe cranial surface of a rat. The sagittal suture runs down the centerof the image. Tumor cells had been injected into the left side some daysearlier so that this animal had developed a glioma on the lefthemisphere of its brain. The right hemisphere was normal. Box 1 liesover the suspected region of brain tumor, while box 2 lies over normaltissue. FIG. 5B is a difference image 1 second after indocyanine greendye had been intravenously injected into the animal. The regioncontaining tumor tissue became immediately visible through the intactcranium. FIG. 5C shows that the dye can be seen to profuse through bothnormal and tumor tissue 5 seconds after dye injection. FIG. 5D showsthat 1 minute after dye injection, the dye had cleared from the normaltissue, but was still retained in the tumor region. The concentration ofdye in the center of this difference image was due to dye circulating inthe sagittal sinus.

FIG. 6 illustrates the change in optical properties over time due to dyeuptake and clearance in tumor vs. non-tumor tissue through the intactskull. Specifically, this is a plot of an average of the percentagechange in optical properties over time averaged over the spatial areasindicated by boxes 1 and 2 from FIG. 5A. The change in signal is afunction of the concentration of dye in the tissue at a particular time.The graphs labeled “extracranial: tumor” and “extracranial: normal” showthe dynamics of the change in optical properties over time within boxes1 and 2, respectively, from FIG. 5A.

FIGS. 7A-7F show a spatial map of dynamic changes in tumor vs. non-tumorareas in a rat glioma model. These images are of the same animal asshown in FIG. 5, however the cranium has now been removed so as toexpose the left hemisphere containing the glioma, and the righthemisphere containing normal tissue. FIG. 7A shows a gray-scale image ofthe area of interest. Box 1 overlays the tumor, Box 2 overlays thetumor-surround, and Box 3 overlays normal tissue. FIG. 7B shows thedifference image of the area of interest 1 second after 1 mg/kg ofindocyanine green had been intravenously injected into the animal.During this initial time, the tumor tissue was the first to show ameasurable optical change, indicating that the uptake of dye occursfirst in the tumor tissue. The gray-scale bar indicates the relativemagnitude of the optical changes in the sequence of difference images.FIGS. 7C and 7D show difference images of the area of interest 4 secondsand 30 seconds, respectively, after dye injection. At these intermediatestages, dye appears to collect in both normal and tumor tissue. FIGS. 7Eand 7F show difference images of the area of interest 1 minute and 5minutes, respectively, after injection of dye. At these later times, dyestill remained in the tumor tissue even though it was being cleared fromnormal tissue.

FIG. 8 shows changes in optical properties over time due to dye uptakeand clearance in tumor vs. non-tumor tissue. Specifically, this is aplot of an average of the percentage change in optical properties overtime averaged over the spatial areas indicated by boxes 1, 2, and 3 inFIG. 7A. The change in optical properties is a function of theconcentration of dye in the tissue at a particular time. The graphslabeled “tumor tissue”, “tumor surround” and “normal brain” are plots ofthe change in optical properties over time within boxes 1, 2 and 3,respectively, from FIG. 7A.

FIGS. 9A-9D demonstrate use of optical imaging of dye uptake to revealresidual traces of tumor cells in resected tumor margins. This is acontinuation of the study on the same animal shown in FIGS. 5 through 8.FIG. 9A shows a higher magnification image of the left hemisphere tumormargin of the animal after the tumor has been resected. Boxes 1 overlayareas that contain small traces of residual tumor cells, and boxes 2overlay areas containing only normal tissue. The gray-scale barindicates the magnitude of optical change in the difference images.FIGS. 9B, 9C, and 9D show difference images of the tumor margin 4, 30,and 60 seconds, respectively, after intravenous dye injection. Minutebiopsies were taken from areas that showed preferred dye containment andfrom areas from which the dye cleared rapidly. These biopsies wereanalyzed blindly and later correlated to the location from which theywere taken. Those biopsies taken from areas which cleared dye were shownto contain only normal cells, whereas biopsies taken from areas whichsequestered dye were shown to contain tumor cells. Extremely smallislands of residual tumor can thus be mapped within tumor margins.

FIG. 10 shows changes in optical properties due to dye uptake andclearance in tumor vs. non-tumor tissue. Specifically, this is a plot ofan average of the percentage change in optical properties over timeaveraged over the spatial areas indicated by boxes 1 and 2 from FIG. 9A.The increase in absorption is a function of the concentration of dye inthe tissue at a particular time. The graphs labeled “margins: tumor ”and “margins:normal” are plots of the change in optical properties overtime within boxes 1 and 2, respectively, from FIG. 9A. These data, aswell as those from FIG. 9, show that the inventive device and method areable to distinguish tumor from non-tumor tissue within tumor marginswith extremely high spatial resolution.

FIG. 11 is a simplified schematic diagram illustrating an apparatus ofthe present invention.

DETAILED DESCRIPTION OF THE INVENTION

Applicants' optical imaging methods and apparatus are described ingreater detail below with reference to certain preferred embodiments.Certain aspects of the optical imaging techniques have been described ineven greater detail in the patents incorporated herein by reference. Thedetailed descriptions of certain preferred embodiments are not intendedto limit the scope of the applicants' invention as described herein andset forth in the appended claims.

Definitions

The following terms, as used in this specification and the appendedclaims, have the meanings indicated:

Area of Interest is an area of tissue that comprises the subject ofacquired data sets. In a preferred embodiment, the area of interest issuspected of containing one or more sites of tumor tissue. The area ofinterest may, for example, be exposed tissue, tissue that underlies oris adjacent exposed tissue, or tissue cultured in vitro.

Arithmetic Logic Unit (ALU) is a component that is capable of performinga variety of processing (e.g., mathematical and logic) operations (e.g.,sum, difference, comparison, exclusive or multiply by a constant, etc.)on a data set.

Control Data is data representing one or more optical properties of thearea of interest during a “normal” or a predetermined period, such asprior to administration of a dye. The control data set establishes a“background” level of optical properties for comparison with asubsequently acquired data set.

Charge Coupled Device (CCD) is a type of optical detector that utilizesa photo-sensitive silicon chip in place of a pickup tube in a videocamera.

Comparison Data is data acquired by comparing subsequent data or dataacquired at a particular time, with control data, such as by adding,subtracting, or the like. The comparison data set is used to identifyand/or locate areas of tumor versus non-tumor tissue.

Electromagnetic Radiation (emr) means energy having a wavelength of fromabout 450 to about 2500 nm. Emr illumination suitable for use in theoptical imaging methods described herein is in the visible and infraredregions.

Frame is a digitized array of pixels.

Frame Buffer is a component that provides storage of a frame, such as acontrol image, a subsequent image or a comparison image.

Geometric Transformations can be used to modify spatial relationshipsbetween data points in a data set, such as pixels in an image. Geometrictransformations are often called “rubber sheet transformations” becausethey can be viewed as the process of “printing” data, such as an image,on a sheet of rubber and stretching the sheet according to a predefinedset of rules. As applied to video imaging, subsequent images can beviewed as having been distorted due to movement and it is desirable to“warp” these images so that they are spatially aligned with the controlimages. Geometric transformations are distinguished from “pointtransformations” in that point transformations modify a pixel's value inan image based solely upon that pixel's value and/or location, and noother pixel values are involved in the transformation. Geometrictransformations are described in the publication Digital ImageProcessing, Gonzalez and Wintz, Addison-Wesley Publishing Co., Reading,1987.

Image is a frame or composition of frames representing one or moreoptical properties of an area of interest.

Optical Properties relate to various properties detectable in the usefulrange of emr (450-2500 nm) including but not limited to scattering(Rayleigh scattering, reflection/retraction, diffraction), absorptionand extinction, birefringence, refractive index, Kerr effect and thelike.

Optical Detector is a device capable of detecting one or more desiredoptical properties of an area of interest. Suitable optical detectorsinclude any type of photon detector, such as photodiodes,photomultiplier tubes, cameras, video cameras, CCD cameras, and thelike.

Optical Imaging refers to the acquisition, comparison, processing anddisplay of data representative of one or more optical properties of anarea of interest. Optical imaging may involve acquisition processing anddisplay of data in the form of images, but need not.

Pixels are the individual units of an image in each frame of a digitizedsignal. The intensity of each pixel is linearly proportional to theintensity of illumination before signal manipulation and corresponds tothe amount of emr (photons) being scattered from a particular area oftissue corresponding to that particular pixel. An image pixel is thesmallest unit of a digital image and its output intensity can be anyvalue. A CCD pixel is the smallest detecting element on a CCD chip andits analog output is linearly proportional to the number of photons itdetects.

Subsequent Data is data representing one or more optical properties ofan area of interest during a monitoring period or subsequent toadministration of a dye.

Tumor Margin is the area where the surgeon has resected a tumor.

Apparatus

The inventive methods employ an apparatus comprising a source of highintensity emr, an optical detector for acquiring data representative ofone or more optical properties of the area of interest, such as videosignals, and image processing capability. The apparatus may beconstructed as an integrated unit, or it may be used as a collection ofcomponents. The apparatus will be briefly described with reference tothe schematic diagram, illustrated in FIG. 11, and various componentsand features will then be described in greater detail.

FIG. 11 illustrates a human patient 10 whose neuronal tissue representsarea of interest 12. As is described in greater detail below, area ofinterest 12 may be fully or partially exposed, or imaging may beconducted through bone and/or dura with proper selection of emrwavelengths. During optical imaging, area of interest 12 is uniformlyilluminated by emr source 14 powered by regulated power supply 16. Emris preferably directed through an optical filter 18 prior to contactingarea of interest 12.

During optical imaging, a light gathering optical element 20, such as acamera lens, endoscope, optical fibers and photon detector 22 or thelike are placed to detect optical properties of area of interest 12.Signals representative of optical properties are processed, if desired,in a gain, offset component 24 and then conveyed to analog-to-digital(A/D) and digital signal processing hardware 26. Data representingoptical properties and particularly changes in optical properties, aredisplayed on display device 28. The optical detection, display andprocessing components are controlled by host computer 30.

An emr source is used for illuminating the area of interest duringacquisition of data representing one or more optical properties. The emrsource may be utilized to illuminate an area of interest directly, aswhen tissue is exposed during or in connection with surgery, or it maybe utilized to illuminate an area of interest indirectly throughadjacent or overlying tissue such as bone, dura, skin, muscle and thelike.

The emr source employed in the present invention is preferably a highintensity, broad spectrum emr source, such as a tungsten-halogen lamp,laser, light emitting diode, or the like. Cutoff filters to selectivelypass all wavelengths above or below a selected wavelength may beemployed. A preferred cutoff filter excludes all wavelengths below about695 nrm. Instead of using cutoff filters, administration of a first dyeprior to administration of a second, different dye can act as a tissuefilter of emr to provide a filter in the area of interest. In thisinstance, it is desirable to utilize a dye that remains with tumor ornormal tissue for a prolonged period of time.

Preferred emr wavelengths for imaging include, for example, wavelengthsof from about 450 nm to about 2500 nm, and most preferably, wavelengthsof the near infrared spectrum of from about 700 nm to about 2500 nm.Generally, longer wavelengths (e.g., approximately 800 nm) are employedto image deeper areas of tissue. Moreover, if a difference image iscreated between the image seen with 500 nm emr and the image seen with700 nm emr, the difference image will show an optical slice of tissue.Selected wavelengths of emr may also be used, for example, when varioustypes of contrast enhancing agents are administered.

The emr source may be directed to the area of interest by a fiber opticmeans. One preferred arrangement provides emr through fiber opticstrands using a beam splitter controlled by a D.C. regulated powersupply (Lambda, Inc.).

The area of interest must be evenly illuminated to effectively adjustthe signal over a full dynamic range, as described below. Nonuniformityof illumination is generally caused by fluctuations of the illuminationsource and intensity variations resulting from the three-dimensionalnature of the tissue surface. More uniform illumination can be providedover the area of interest, for example, by using diffuse lighting,mounting a wavelength cutoff filter in front of the optical detectorand/or emr source, or combinations thereof. Fluctuation of theillumination source itself is preferably addressed by using a lightfeedback mechanism to regulate the power supply of the illuminationsource. In addition, a sterile, optically transparent plate may contactand cover the area of interest to provide a flatter, more even contour.The plate also diminishes tissue movement. Fluctuations in illuminationcan be compensated for by using image processing algorithms, includingplacing a constant shade gray image marker point at the area of interestas a control point.

The apparatus also comprises an optical detector for acquiring a signalrepresentative of one or more optical properties of the area ofinterest. Any photon detector may be employed as an optical detector.Specialized detectors suited for detecting selected optical propertiesmay be employed. One preferred optical detector for acquiring data inthe format of an analog video signal is a charge coupled device (CCD)video camera which produces an output video signal at 30 Hz having, forexample, 512 horizontal lines per frame using standard RS 170convention. One suitable device is a CCD-72 Solid State Camera (Dage-MTIInc., Michigan City Ind.). Another suitable device is a COHU 6510 CCDMonochrome Camera with a COHU 6500 electronic control box (COHUElectronics, San Diego, Calif.). In some cameras, the analog signal isdigitized 8-bits deep on an ADI board (analog-to-digital board). The CCDmay be cooled, if necessary, to reduce thermal noise.

The optical imaging methods of the present invention may also usefullyemploy non-continuous illumination and detection techniques. Forexample, short pulse (time domain), pulsed time, and amplitude modulated(frequency domain) illumination sources may be used in conjunction withsuitable detectors (See, Yodh, A., and Chance, B. Physics Today, March,1995). Frequency domain illumination sources typically comprise an arrayof multiple source elements, such as laser diodes, with each elementmodulated at 180° out of phase with respect to adjacent elements (see,Chance, B. et al., (1993) Proc. Natl. Acad. Sci. USA, 90, 3423-3427).Two-dimensional arrays, comprising four or more elements in twoorthogonal planes, can be employed to obtain two-dimensionallocalization information. Such techniques are described in U.S. Pat.Nos. 4,972,331 and 5,187,672 which are hereby incorporated by reference.

Time-of-flight and absorbance techniques (Benaron, D. A. and Stevenson,D. K. (1993) Science, 259, 1463-1466) may also be usefully employed inthe present invention. In yet another embodiment of the presentinvention, a scanning laser beam may be used in conjunction with asuitable detector, such as a photomultiplier tube, to obtain highresolution images of an area of interest.

Illumination with a part of the infrared spectrum allows for imagingintrinsic signals through tissue overlying or adjacent the area ofinterest, such as dura and skull. One exemplary infrared emr sourcesuitable for imaging through tissue overlying or adjacent the area ofinterest is a Tunable IR Diode Laser from Laser Photonics, Orlando, Fla.When using this range of far infrared wavelengths, the optical detectoris preferably provided as an infrared (IR) detector. IR detectors aremade from materials such as indium arsenide, germanium and mercurycadmium telluride, and are generally cryogenically cooled to enhancetheir sensitivity to small changes in infrared radiation. One example ofan IR imaging system which may be usefully employed in the presentinvention is an IRC-64 infrared camera (Cincinnati Electronics, MasonOhio).

Image (data) processing is an important feature of the optical imagingtechniques and apparatus of the present invention. In use, for example,a CCD apparatus is preferably adjusted (at the level of the analogsignal and before digitizing) to amplify the signal and spread thesignal across the full possible dynamic range, thereby maximizing thesensitivity of the apparatus. Specific methods for detecting opticalsignals with sensitivity across a full dynamic range are described indetail in the patents incorporated herein by reference. Means forperforming a histogram stretch of the difference frames (e.g.,Histogram/Feature Extractor HF 151-1-V module, Imaging Technology,Woburn Mass.) may be provided, for example, to enhance each differenceimage across its dynamic range. Exemplary linear histogram stretches aredescribed in Green, Digital Image Processing: A Systems Approach, VanNostrand Reinhold, N.Y., 1983. A histogram stretch takes the brightestpixel, or one with the highest value in the comparison image, andassigns it the maximum value. The lowest pixel value is assigned theminimum value, and every other value in between is assigned a linearvalue (for a linear histogram stretch) or a logarithmic value (for a loghistogram stretch) between the maximum and minimum values. This allowsthe comparison image to take advantage of the full dynamic range andprovide a high contrast image that clearly identifies areas of tumortissue.

Noise (such as 60 Hz noise from A.C. power lines) is filtered out in thecontrol box by an analog filter. Additional adjustments may furtherenhance, amplify and condition the analog signal from a CCD detector.One means for adjusting the input analog signal is to digitize thissignal at video speed (30 Hz), and view the area of interest as adigitized image that is subsequently converted back to analog format.

It is important that data, such as consecutive images of a particulararea of interest, be aligned so that data corresponding to the samespatial location can be compared. If an averaged control image and asubsequent image are misaligned prior to comparison, artifacts will bepresent and the resulting comparison image will be more like a gradientimage that amplifies noise and edge information. Image misalignment canbe caused by patient motion, heartbeat and respiration. Large patientmovements may require a new orientation of the camera and acquisition ofa new averaged control image. It is possible, however, to compensate forsmall tissue movements by either mechanical or computational means, or acombination of both.

One way to reduce relative movement of the optical detector and the areaof interest is to rigidly secure the optical detector, and possibly theemr source, to the skeletal frame of the patient, such as by postsmounted on the cranium. The optical detector and emr source may also beprovided as an integral unit to reduce relative motion. Other means formaintaining the optical detector and the illumination source in aconstant orientation with respect to the area of interest may also beemployed.

Real-time motion compensation and geometric transformations may be usedto align corresponding data. Simple mechanical translation of data ormore complex (and generally more accurate) geometric transformationtechniques can be implemented, depending upon the input data collectionrate and amount and type of data processing. For many types of images,it is possible to compensate by a geometrical compensation whichtransforms the image by translation in the x-y plane. In order for analgorithm such as this to be feasible, it must be computationallyefficient (preferably implementable in integer arithmetic), memoryefficient, and robust with respect to changes in ambient light.

For example, functional control points can be placed in the area ofinterest and triangulation-type algorithms used to compensate formovements of these control points. Control points can be placed directlyin the area of interest, such as directly on the cortical surface.Goshtasby (“Piecewise Linear Mapping Functions for Image Registration”in Pattern Recognition vol. 19 pp 459-66, 1986) describes a methodwhereby an image is divided into triangular regions using controlpoints. A separate geometrical transformation is applied to eachtriangular region to spatially register each control point to acorresponding triangular region in a control image.

“Image warping” techniques may be employed whereby each subsequent imageis registered geometrically to the averaged control image to compensatefor movement. Image warping techniques described in, for example,Wolberg, “Digital Image Warping” IEEE Computer Society Press, LosAlimitos, Calif. 1990, may be used. Image warping techniques can furtherindicate when movement has become too great for effective compensationand a new averaged control image must be acquired.

The data processing function is generally operated and controlled by ahost computer. The host computer may comprise any general computer (suchas an IBM PC type with an Intel 386, 486 Pentium or similarmicroprocessor or Sun SPARC) that is interfaced with the emr sourceand/or optical detector and directs data flow, computations, imageacquisition and the like. Thus, the host computer controls acquisitionand processing of data and provides a user interface.

According to a preferred embodiment, the host computer comprises asingle-board embedded computer with a VME64 interface, or a standard(IEEE 1014-1987) VME interface, depending upon bus band widthconsiderations. Host computer boards which may be employed in thepresent invention include, for example, Force SPARC/CPU-2E and HP9000Model 7471. The user interface can be, for example, a Unix/X-Windowenvironment. The image processing board can be, for example, based uponTexas Instruments' MVP and other chips to provide real-time imageaveraging, registration and other processing necessary to produce highquality difference images for intraoperative viewing. This board willalso drive a 120×1024 RGB display to show a sequence of differenceimages over time with pseudo-color mapping to highlight tumor tissue.Preferably, a second monitor is used for the host computer to increasethe overall screen real estate and smooth the user interface. Theprocessing board (fully programmable) can support a VME64 masterinterface to control data transactions with the other boards. Lastly, aperipheral control board can provide electrical interfaces to controlmechanical interfaces from the host computer. Such mechanical interfacescan include, for example, the light source and optical detector controlbox.

A real-time data acquisition and display system, for example, maycomprise four boards for acquisition, image processing, peripheralcontrol and host computer. A minimal configuration with reducedprocessing capabilities may comprise just the acquisition and hostcomputer boards. The acquisition board comprises circuitry to performreal-time averaging of incoming video frames and allow readout ofaveraged frames at a maximum rate bus. A VME bus is preferred because ofits high peak bandwidth and compatibility with a multitude of existingVME products. The acquisition board should also support many differenttypes of optical detectors via a variable scan interface. A daughterboard may support the interfacing needs of many different types ofoptical detectors and supply variable scan signals to the acquisitionmotherboard. Preferably, the unit comprises a daughter board interfacingto an RS-170A video signal to support a wide base of cameras. Othercamera types, such as slow scan cameras with a higher spatial/contrastresolution and/or better signal to noise ratio, can be developed andincorporated in the inventive device, as well as improved daughterboards to accommodate such improved cameras.

According to a preferred embodiment, data, such as analog video signals,are continuously processed using, for example, an image analyzer (e.g.,Series 151 Image Processor, Imaging Technology, Inc., Woburn Mass.). Animage analyzer can receive and digitize an analog video signal with ananalog to digital interface and perform such a function at a frame speedof about {fraction (1/30)}th of a second (e.g., 30 Hz or “video speed”).Processing the signal involves first digitizing the signal into a seriesof pixels or small squares assigned a value (in a binary system)dependent upon the number of photons (i.e., quantity of emr) beingdetected from the part of the area of interest assigned to that pixel.For example, in a standard 512×512 image from a CCD camera, there wouldbe 262,144 pixels per image. In an 8 bit system, each pixel isrepresented by 8 bits corresponding to one of 256 levels of gray.

The signal processing means preferably includes a programmable look-uptable (e.g., CM150-LUT16, Imaging Technology, Inc., Woburn, Mass.)initialized with values for converting gray coded pixel values,representative of a black and white image, to color coded values basedupon the intensity of each gray coded value. This can provide imageenhancement via an image stretch. An image stretch is a techniquewhereby the highest and lowest pixel intensity values used to representeach of the pixels in a digital image frame are determined over a regionof the image frame which is to be stretched. Stretching a selectedregion over a larger range of values permits, for example, easieridentification and removal of relatively high, spurious values due tonoise (e.g., glare).

The processing means may further include a plurality of frame buffershaving frame storage areas for storing frames of digitized image datareceived from the analog/digital interface. The frame storage areacomprises at least one megabyte of memory space, and preferably at least8 megabytes of storage space. An additional 16-bit frame storage area ispreferred as an accumulator for storing processed image frames havingpixel intensities represented by more than 8 bits. The processing meanspreferably includes at least three frame buffers, one for storing theaveraged control image, another for storing the subsequent image, and athird for storing a comparison image.

According to preferred embodiments, the processing means furthercomprises an arithmetic logic unit (e.g., ALU-150 Pipeline Processor)for performing arithmetical and logical functions on data located in oneor more frame buffers. An ALU may, for example, provide image (data)averaging in real time. A newly acquired digitized image may be sentdirectly to the ALU and combined with control image stored in a framebuffer. A 16 bit result can be processed through an ALU, which willdivide this result by a constant (i.e., the total number of images). Theoutput from the ALU may be stored in a frame buffer, further processed,or used as an input and combined with another image.

The comparison (e.g., difference) data is, preferably, further processedto smooth out the image and remove high frequency noise. For example, alowpass spatial filter can block high spatial frequencies and/or lowspatial frequencies to remove high frequency noises at either end of thedynamic range. This provides a smoothed-out processed difference image(in digital format). The digitally processed difference image can becolor-coded by assigning a spectrum of colors to differing shades ofgray. This image is then converted back to an analog image (by an ADIboard) and displayed for a real time visualization of differencesbetween an averaged control image and subsequent images. Moreover, theprocessed difference image can be superimposed over the analog image todisplay specific tissue sites where a dye or contrast enhancing agentmay have a faster uptake.

Processing speed may be enhanced by adding a real time modular processoror faster CPU chip to the image processor. One example of a real timemodular processor which may be employed in the present invention is a150 RTMP-150 Real Time Modular Processor (Imaging Technology, Woburn,Mass.).

The processing means may further include an optical disk for storingdigital data, a printer for providing a hard copy of the digital and/oranalog data and a display, such as a video monitor to permit thephysician to continuously monitor the comparison data output.

A single chassis may house all of the modules necessary to provideoptical imaging according to the present invention. The necessarycomponents, whether or to whatever degree integrated, may be installedon a rack that is easily transportable within and between operating andhospital rooms along with display monitors and peripheral input andoutput devices.

Imaging Methods

The method for imaging a solid tumor involves periodically administeringa dye by bolus injection into vasculature (e.g., artery or vein)perfusing the suspected tumor site in the area of interest. Preferably,the dye has a relatively short half life (e.g., less than five minutes)and is rapidly cleared to allow for repeated administration. An opticaldetector, such as a video CCD, is focused upon the suspected solid tumorsite (area of interest) and high intensity emr containing a wavelengthwhich interacts with the dye illuminates the site. The form ofinteraction between the emr and the dye will depend on the specific dyebeing used. For example, in the case of a fluorescent dye, the preferredwavelength of emr is one which excites the dye, thereby causingfluorescence. However with some dyes, such as indocyanine green, thepreferred wavelength of emr is one which is absorbed by the dye. Justprior to administration of the dye, the first averaged image, or controlimage is taken, digitized and stored in a frame buffer. The dye isinjected quickly and rapidly as a bolus. Subsequent image frames aretaken and stored and subtractively compared to produce comparison, ordifference, images (e.g., one or two per second) using the inventiveprocessing means.

Initial visualization of the dye will appear in the comparison imagefirst in tumor tissue because the dye perfuses more rapidly into tumortissue than non-tumor tissue. Solid tumor margins will be the firstimages to appear in the comparison image as darkened lines outlining asolid tumor mass. This comparison image can be frozen and stored toallow the surgeon to study the tumor image and identify tumor margins inreal time during an operation. The dye will remain for a longer periodof time in tumor tissue compared to normal tissue. Therefore, afterthere is general appearance of the dye throughout the area of interestin both normal tissue and tumor tissue, the dye clearance in tumortissue will be delayed, allowing another opportunity to visualize tumormargins by dye presence in tumor tissue but not in normal tissue.

The more aggressive or malignant the tumor (higher tumor grade), thelonger the dye remains in the tumor tissue. For lower grade or morebenign tumors, the dye remains in tumor tissue for 45 sec to 2 min,whereas the dye can remain in more malignant tumors for up to 10minutes.

In an alternative embodiment of the present invention, solid tumortissue may be distinguished from non-tumor tissue and characterized byadministering a dye to the area of interest, illuminating the area ofinterest with emr containing a wavelength that interacts with the dye,and detecting differences in one or more optical properties between thetumor tissue and non-tumor tissue.

The inventive method is superior to established tumor imagingtechniques, such as MRI, because it can optically image and distinguishlow grade tumors that cannot be distinguished with current MRItechniques, and updated images are continually available during asurgical procedure by readministering the dye. The dye can beadministered on multiple occasions during a surgical procedure afterresection has begun to look at resected walls for residual tumor tissue.For CNS tumors, MRI techniques can only image advanced stage tumors thathave compromised the blood brain barrier. The present optical imagingmethod, by contrast, can image even low grade tumors that have not yetcompromised the blood brain barrier.

The dye can be any emr-absorbing or fluorescent dye that is safe for invivo administration, and has a short half-life when administeredintravenously or intraarterially. Further, during surgical resection ofa solid tumor, it is important that the dye be rapidly cleared from thearea of interest so that dye can be administered repeatedly to imageresidual tumor tissue. Dyes suitable for use with the present inventioninclude indocyanines, fluoresceins, hematoporphyrins, fluoresdamine andother dyes used for photodynamic treatment of tumor tissue, such asthose available from Quadra Logic Technologies, Inc. (Vancouver, B.C.).Specific examples of dyes which may be usefully employed with thepresent invention include indocyanine green, PHOTOFRIN®) ahematoporphyrin dye, NPe₆, BPD, Evans Blue, BIODIPY® dyes, a series offluorophores; (available from Molecular Probes, Inc., Eugene, Oreg.) andcombinations thereof.

Without being bound by theory, the dynamic differences in dye perfusionthrough normal brain tissue surrounding and tumor tissue could beaccounted for by any one or a combination of the following four reasons:(1) greater extravasation of the dye through leaky tumor capillaries;(2) more rapid uptake of the dye by tumor tissue; (3) slower transittimes through tumor tissue; and (4) preferential uptake of the dye bytumor cells.

Microvasculature in the rat glioma model has been examined and comparedto normal cortex. Blood flow in tumor tissue is slower and more variablethan in normal tissue. These differences have been attributed to tumorlocation, degree of infiltration, and necrosis. In other studies usingcultured spheroids of C6 astroglial cells transplanted into rat brain,blood flow was slower in viable tumor than in normal rat brain.Microvessel volume fraction was equivalent between tumor and normalbrain. However, since only about 50% of the tumor was actively perfused,the surface area of perfused microvessels in the tumor was one-half thatof the normal brain. These changes could account for a slower flow ofdye through the tumor compared to normal brain and also lead to morerapid clearance by the normal brain in contrast to the tumor.

The permeability of tumor capillaries is much higher than that of normalbrain. This leakiness of tumor capillaries leads to extravasation oflarger particles is resulting in edema and an increase in interstitialpressure surrounding tumor microvessels. Since tumor microvessels do notcontain normal arteriole smooth muscle, they also have no local controlof pressure gradients. This leads to a stasis of flow in tumor tissue.The overall effect on dye perfusion is longer transit times than innormal brain. Such reasoning supports the dynamic changes in opticalproperties in tumor and normal tissue that are seen during dyeperfusion. There is nearly equivalent uptake, but a much slower transittime in tumor tissue, resulting in prolonged increases in opticalproperties compared to normal tissue. Also, tissue surrounding the tumoris expected to have increased interstitial pressures but without leakycapillaries and other microvasculature changes, thereby accounting forthe fact that tumor margin tissue has an intermediate duration ofoptical changes.

Yet another aspect of the inventive method involves using an emrabsorbing or fluorescent dye conjugated to a targeting molecule, such asan antibody, or more particularly, a monoclonal antibody or fragmentthereof specific for an antigen surface marker of a tumor cell. The areaof interest is illuminated with emr containing excitation wavelengths ofthe fluorescent dye but not emission wavelengths. This can beaccomplished by use of a cutoff filter over the emr source. Preferably,the optical detector is coupled to an image intensifier or micro channelplate (e.g., KS-1381 Video Scope International, Wash D.C.) to increasethe sensitivity of the system by several orders of magnitude and allowfor visualization of cells having fluorescent dyes attached thereto.Examples of fluorescent dyes that can be conjugated to a targetingmolecule include, for example, Cascade Blue, Texas Red and LuciferYellow CH from Molecular Probes, Eugene, Oreg.

The methods and apparatus described herein for optical imaging of tumortissue can operate outside of a surgical procedure setting. Morespecifically, it is possible to optically image tissue through intactskin and bone. In some areas of the body, longer wavelength visiblelight and near infrared emr can easily pass through tissue, such asbreast tissue. With dye injection, areas of increased vascularity, suchas tumor tissue can be identified. The optical imaging techniques of thepresent invention can therefore be used, for example, to screen fortumors in breast and other tissue.

EXAMPLE 1

This example illustrates optical imaging of a low grade CNS tumor(astrocytoma, grade 1) using the methods and apparatus of the presentinvention. A MRI scan was conducted before the operation. However,tumors of this type and grade are notoriously difficult to distinguishfrom normal tissue once the surgical removal of the tumor has begun.

All imaging procedures reported in this and in the following exampleswere reviewed and approved by the University of Washington HumanSubjects Review Committee. All patients signed an informed consent formfor both the surgery and the imaging experiments.

The imaging procedure used in Examples 1-4 was as follows. The area ofinterest was evenly illuminated by a fiber optic light source with theradiation passing through a beam splitter, controlled by a D.C.regulated power supply (Lambda, Inc.) and passed through a 695 nmlongpass filter. Images were acquired with a CCD camera (COHU 6500)fitted to the operating microscope with a specially modifiedcineadaptor. The cortex was stabilized with a glass footplate. Imageswere acquired at 30 Hz and digitized at 8 bits (512×480 pixels, using anImaging Technology, Inc. Series 151 system, Woburn, Mass.). Geometricaltransformations were applied to images to compensate for small amountsof patient motion (Wohlberg, Digital Imaging Warping, I.E.E.E. ComputerSociety, Los Alamitos, Calif., 1988). Subtraction of images collectedfollowing dye administration from those collected during a control statewith subsequent division by the control image resulted in percentagedifference maps. Raw data (i.e., no digital enhancement) were used fordetermining the average optical change in specified regions (averagesize box was 30×30 pixels or 150-250 um²). For pseudocolor images, alinear low pass filter removed high frequency noise and linear histogramtransformations were applied. Noise was defined as the standarddeviation of fluctuations in sequentially acquired control images as0.003-0.009.

An averaged control image was obtained of the particular corticalsurface area of interest. FIG. 1A is a gray-scale image of the area ofinterest prior to dye administration. The lettered labels placed uponthe brain by the surgeon overlay the tumor as identifiedintraoperatively by ultrasound. Indocyanine green dye (1 mg/kg) wasadministered into a peripheral intravenous catheter as a bolus at time0. FIG. 1B shows a difference image taken approximately 15 seconds afterintravenous injection of dye. FIG. 1C shows the difference image about30 seconds after dye administration. The area of the tumor tissue showedthe first tissue staining. FIG. 1D shows that with this low grade tumor,all tissue (both normal and abnormal) showed staining at 45 sec afterdye administration. FIG. 1E is an image of the area of interest oneminute after dye administration and FIG. 1F is the image five minutesafter dye administration showing complete clearance in this low gradetumor. In all the examples presented herein demonstrating opticalimaging in humans, each image covers an area of approximately 4 cm×4 cm.

These data show that indocyanine green enters low grade tumor tissuefaster than normal brain tissue, and may take longer to be cleared frombenign tumor tissue than normal tissue. Therefore, it is possible toimage even low grade tumors with this apparatus. Furthermore, it ispossible to distinguish low grade tumor tissue from surrounding normaltissue intraoperatively. Subsequent pathology of this tumor tissueestablished it as a low grade glioma.

EXAMPLE 2

This example illustrates optical imaging of a highly malignant CNS tumor(glioblastoma; astrocytoma, grade IV). FIG. 2A shows a gray-scale imagein which malignant brain tumor tissue was densest in the center and tothe right but that the tissue elsewhere was mostly normal. Thisillustrates that the optical imaging methods and apparatus of thepresent invention may be employed to distinguish between tumor andnon-tumor tissue without the use of contrast enhancing agents, followingoptimization of the gain and offset on the photodetector. However, ahigher resolution is obtained with the use of contrast enhancing agents.The imaging data were confirmed by pathology slides and flow cytometrydata available one week after surgery. FIG. 2B is the difference imageat 15 seconds after intravenous injection of indocyanine green, showingthat the dynamics of dye perfusion in the first seconds in malignanttissue are similar to those in the first few seconds in benign tumortissue. FIG. 2C shows that at 30 seconds the dye uptake in malignanttissue is even more intense by comparison to the normal tissue. FIG. 2D(1 minute after dye injection) and 2E (10 minutes after dye injection)show that dye is retained significantly longer in malignant tissue thanin benign tumor tissue and, in some cases, continues to sequester in themalignant tumor tissue over longer periods of time. Therefore, using theapparatus and methods of the present invention, it is possible toidentify malignant tumor tissue, distinguish intraoperatively betweennormal and malignant tumor tissue, and to distinguish between thevarious grades of tumor (e.g., normal vs. benign vs. malignant). Thus,it is possible to not only image the location and margins of tumortissue, but also to grade the tumor with more malignant tumors retainingdye for a longer period of time than lower grade tumors.

EXAMPLE 3

This example illustrates optical mapping of the margins of a malignantCNS tumor. FIG. 3 shows a series of images and difference images of thearea of interest taken after surgical removal of the tumor and when thearea was thought to be free of tumor tissue. Normally, in this size of aresection margin, only a single frozen sample would be taken forpathology analysis. For the purpose of this study, five biopsies weretaken from the margin to aid in correlating the histology with the mapobtained by the invention. FIG. 3A shows a gray-scale image of the tumormargin. FIG. 3B shows the margin with labels that the surgeon placeddirectly on the brain to identify where the surgeon was going to removebiopsy samples for histological analysis after difference images wereacquired with the inventive device. FIG. 3C shows the difference image 1minute after intravenous injection of dye and FIG. 3D shows thedifference image 10 minutes after dye injection. These is post-dyedifference images reveal a number of sites that contain tumor tissue aswell as areas of normal tissue. The accuracy of the optical imaging wasconfirmed post operatively by analysis of the biopsies. Note that asmall area on the lower right of FIG. 3D indicates a possible region oftumor tissue that would not have been biopsied by the surgeon. Thesedata show that the invention is able to identify small remnants of tumortissue in a tumor margin after resection of a tumor. In addition, theinvention could act as an aid to removing biopsies from the site of atumor margin, thereby reducing the sampling error associated with thepresently used random sampling technique.

EXAMPLE 4

This example illustrates that the methods and apparatus of the presentinvention can be used to characterize and identify tumor tissue thatdoes not contrast enhance with traditional MRI imaging. Lack of MRIenhancement is usually typical of benign tumors. However, a proportionof non-benign tumors are not observable with s present MRI imagingtechniques. The images in FIG. 4 are from a patient whose tumor did notcontrast enhance with MRI. However, optical imaging was able to identifythis tumor as a non-benign type. Pathology and flow cytometry dataavailable one week after surgery confirmed that this tumor was ananoplastic astrocytoma. FIG. 4A shows the gray-scale image of the areaof interest. FIG. 4B shows the difference image prior to dye injection.FIG. 4C shows the area of interest 1 minute after intravenous dyeinjection, and FIG. 4D shows the area of interest 5 minutes after dyeinjection. Note that the dye is retained in this tissue for asignificant time. As shown in FIGS. 1, 2, and 3, this dynamic trait is acharacteristic of a non-benign tumor.

EXAMPLE 5

This example illustrates a series of experiments using a rat gliomamodel intraoperatively to investigate whether the inventive methods anddevice could function in an operating room setting to provide real timeinformation to the surgeon regarding resection of all tumor tissue.

The rat glioma model is a standard predictive model and was used todelineate dye uptake, clearance and overall parameters of opticalimaging that result in the best images. The advantages of this model arethe ability to consistently get reproducible tumors for imaging studiesand to resect tumor under an operating microscope and still findresidual tumor with the inventive optical imaging. A disadvantage ofthis model is the more sarcoma-like appearance of the tumor and a lesserdegree of vascularity compared to human gliomas.

Briefly, the rat glioma model uses an ethylnitrosourea-induced F-344 rattumor line developed from a clonal population of a spinal malignantastrocytoma. This tumor is similar to human astrocytomas microscopicallyand in vivo, because both have stellate-shaped cells in the brainparenchyma and both have intracytoplasmic filaments 80-100 mm indiameter as seen by scanning electron microscopy. The glioma cells weremaintained in Weymouth's medium supplemented with 10% fetal calf serum.Viable cells (5×10⁴) were trypsinized from a monolayer culture andimplanted stereotaxically into the right cerebral hemisphere of 30syngeneic female rats, each weighing 140-160 g. The stereotaxiccoordinates for right frontal lobe implantation were 4.5 mm anterior tothe frontal zero plane, 3 mm right from the midline and 6 mm deep. Therats were anesthetized for implantation. The heads were shaved andscalps opened, and a 1 mm burr hole made at the appropriate coordinates.The cells were injected through a 27 gauge needle, the needle left inplace for 30 sec post injection and the hole was covered with bone wax.The scalp was sutured and the animals observed for 3-4 hrs until theyreturned to normal activity and feeding. The animals were used 10-14days after tumor implantation. In this model, animals begin to showclinical symptoms from the tumor by 16-19 days, such as decreasedactivity and feeding, hemiparesis and eventually succumb between19-27days from mass effects due to tumor expansion.

Fourteen animals underwent complete study, including imaging before andafter resection of the tumor. The animals were anesthetized with 2%isoflurane, and the femoral vein cannulated for administration of thedye. Anesthesia was maintained with a-chloralose (50 mg/kg administeredip) and urethane (160 mg/kg administered ip). The animals were placed ina stereotaxic holder. Imaging studies were then carried out before orafter removal of the cranium. The tumor typically occupied the anteriorone half to two thirds of the right hemisphere exposure. The compressedbrain without any tumor infiltration was defined as the tumor surroundto separate it from the normal hemisphere on the contralateral side.

Following imaging of the area of interest, an operating microscope wasused to attempt gross total removal of the tumor. Sites were then chosenfor biopsy based on optical imaging results and later analyzedhistologically. The biopsy specimens were fixed in 10% paraformaldehyde,Nissl stained and mounted. All specimens were read blindly and labeledeither positive or negative for tumor. These data were correlated to theoptical imaging results to identify residual tumor and statisticalanalysis (Chi square or student t-test) was performed to determine thesignificance of the results.

The following imaging apparatus was employed in Examples 5 and 6. Lightwas from a tungsten-halogen bulb regulated by a D.C. power supply,passed through a longpass filter (690 nm), and through a right angledprism reflected through a 50 or 100 mm objective lens onto the corticalsurface. The reflected light was collected by the same objective lensand focused by a projection lens onto the surface of a CCD camera (COHU6300). The imaging apparatus was attached to the stereotaxic frame whichwas rigidly fixed to a vibration isolation table. Specially designedautomatic warping algorithms were designed to compensate for smallamounts of movement. Images (512×480 pixels) were acquired at 30 Hz anddigitized at 8 bits (256 gray levels). Every 2 sec, a single imagecomprising 30 averaged frames was collected (1 sec) and then stored (1sec).

Control images were collected prior to intravenous injection ofindocyanine green dye at a dose of 1 mg/kg and then for 2 min after dyeinjection. The dye injection was made over a 1 sec period while the lastcontrol image was being stored. A period of 20 min was allowed betweendye injections to allow optical images to return to baseline. Theinitial control images of each trial were subtracted from each other toinsure that the baseline starting point of each trial was equivalent.

A single control image was chosen and then subtracted from each of thecontrols (4-6 images) and each of the post-dye injection images. Theresultant image was divided by the original control image and multipliedby 100 to give a composite percentage difference for the entire sequencebefore and after dye injection. The optical change that occurred betweenseparate control images were 0.2-0.7%, whereas the peak changesresulting from dye injection were in the range of 5-40%. The spatialresolution of an individual pixel in the image ranged from 13.5×11.7 mm²to 27×25.4 mm². Boxes measuring from 15-30 pixels per side were drawn onthe images. The average percentage change in the individual boxes wascalculated and used to demonstrate graphically the optical changes overtime in the different types of tissue.

Imaging studies were performed on fourteen animals. The time course ofdye perfusion through the tissue had a dynamic aspect. Optical imagingof indocyanine green dye perfusion at a dose of 1 mg/kg in 16 separateruns from a cortical surface in 9 different animals demonstrated thedynamic nature of the optical changes. In all the rat imaging examplespresented herein, each image covers an area no greater thanapproximately 1 cm×1 cm. FIG. 7 illustrates the dynamic differences inchanges in optical property due to dye absorption between tumor andnon-tumor tissue. This is the same animal as shown in FIG. 5 (see,Example 6), however the cranium has now been removed so as to expose theleft hemisphere containing the glioma, and the right hemispherecontaining normal tissue. FIG. 7A shows a gray-scale image of the areaof interest. Box 1 overlays the tumor, Box 2 overlays thetumor-surround, and Box 3 overlays normal tissue. FIG. 7B shows thedifference image of the area of interest 1 second after administrationof indocyanine green. During this initial time, the tumor tissue is thefirst to show a measurable optical change, indicating that the uptake ofdye occurs first in the tumor tissue. The gray-scale bar indicates therelative magnitude of the optical changes in the sequence of differenceimages. FIGS. 7C and 7D show difference images of the area of interest 4seconds and 30 seconds, respectively, after dye injection. At theseintermediate stages dye appears to collect in both normal and tumortissue. FIGS. 7E and 7F show difference images of the area of interest 1minute and 5 minutes, respectively, after injection of dye. At theselater times, it becomes clear that dye is still collecting in tumortissue even though it is being cleared from normal tissue.

The optical signals begin to change within the first 2-3 seconds afterdye injection and peak 6 seconds after injection in all three areas,tumor tissue, tumor-surround and normal brain. However, the threedifferent tissue types are differentiated by the rate of rise over thefirst four seconds, the peak optical change reached, and the eventualplateau that occurs after the first 30 seconds. The tumor tissue had asignificantly greater peak percentage difference change than the tumorsurround which in turn had a greater peak percentage different changethan the normal brain. For example, following maximization of the gainand offset on the camera controls, the peak percentage differencechanges were as follows: tumor 40.5±9.6%; tumor surround 16.4±6.8%; andnormal brain 9.7±4.7%.

FIG. 8 is a plot of an average of the percentage change in opticalproperties over time averaged over the spatial areas indicated by boxes1, 2, and 3 from FIG. 7A. The change in optical property is a functionof the concentration of dye in the tissue at a particular time. Thegraphs labeled “tumor tissue”, “tumor surround” and “normal brain” areplots of the change in optical properties over time within boxes 1, 2,and 3, respectively, from FIG. 7A. These data, as well as those fromFIG. 7, show that the inventive method and device is able to distinguishnot only tumor from non-tumor tissue, but also tumor-surround areaswhich contain varying densities of tumor versus normal cells.

Since the peak optical change was always reached 4-6 seconds after dyeinjection, there was also a significantly faster rate of optical changein the tumor tissue compared to the tumor surround or the normal brain.A more rapid onset of dye perfusion into the tumor tissue was displayedas a faster time course. The tumor tissue had a more rapid and greaterrise time than either the tumor surround or normal brain (p<0.01).

In 13 of 14 animals there was a prolonged increase (>2 min) in theoptical signal in the tumor after the normal and tumor surround tissuehad returned to baseline. Finally, even the normal and tumor surroundtissue were significantly different in dye uptake (rise time: normal2.4%/sec; tumor surround 4.0%/sec). Therefore, the dynamic features ofdye uptake and clearance are critical for determining the type of tissuewhen imaging resection margins.

The rat glioma model also provided an opportunity to image resectionmargins once all visible tumor had been removed. FIG. 9A shows a highermagnification image of the left hemisphere tumor margin of the animalafter the tumor had been resected. Boxes 1 overlay areas that containedsmall traces of residual tumor cells, and boxes 2 overlay areas thatcontained only normal tissue. The gray-scale bar indicates the magnitudeof optical change in the difference images. FIGS. 9B, 9C, and 9D showdifference images of the tumor margin 4, 30, and 60 seconds afterintravenous dye injection, respectively. Minute biopsies were taken fromareas that showed preferred dye containment and from areas from whichthe dye cleared rapidly. These biopsies were analyzed blindly and latercorrelated to the location from which the biopsies were taken. Thosebiopsies taken from areas which cleared dye were shown to contain onlynormal cells, whereas biopsies taken from areas which sequestered dyewere shown to contain tumor cells.

The more rapid rate of rise seen in cortical surface imaging was stillpresent for the resection margins that were positive for tumor comparedto normal brain. Again, significant differences between the tumor andthe normal brain existed for the rate of rise, peak optical change, andplateau 60 seconds after dye injection (all p<0.01). FIGS. 6-9demonstrate that the inventive method and device can be used incombination with multiple injections of dye for repeated applicationthroughout a tumor resection surgery (in this case, 4 separateinjections of dye were given). Furthermore, extremely small islands ofresidual tumor can be mapped within the tumor margins.

Sensitivity and specificity of optical imaging was determined for 34samples (n=12 animals). Of 15 biopsy sites deemed negative for tumor byoptical imaging, 14 of the 15 were clear of tumor by histologicalanalysis (sensitivity 93%). Most of the specimens that were negative fortumor were taken from the posterior wall of the tumor resection cavityor the depth of the cavity (where the hippocampus or denate gyrus werefrequently biopsied). Of 19 biopsy sites deemed positive for tumor byoptical imaging, 17 of the biopsy specimens were read as positive fortumor (specificity 89.5%). The two sites that were negative for tumor onhistology but positive for tumor by optical imaging had increasedcellularity but were deemed negative for tumor because there was nofocus of tumor tissue present. The overall significance of these resultsare p<0.001.

FIG. 10 shows changes in optical properties due to dye uptake andclearance in tumor vs. non-tumor tissue. Specifically, this is a plot ofan average of the percentage change in optical properties over timeaveraged over the spatial areas indicated by boxes 1 and 2 from FIG. 9A.The increase in absorption is a function of the concentration of dye inthe tissue at a particular time. The graphs labeled “margins: tumor” and“margins: normal”, are plots of the changes in optical properties overtime within boxes 1 and 2, respectively, from FIG. 9A. These data, aswell as those from FIG. 9, show that the inventive device and method areable to distinguish tumor from non-tumor tissue within tumor marginswith extremely high spatial and temporal resolution.

EXAMPLE 6

A series of experiments was performed using the rat glioma modeldescribed in Example 5 to investigate whether the inventive methods anddevice could image tumor tissue through an intact skull and throughintact skin prior to or after surgery. Imaging of tumor tissue wasattempted through the intact skull of the rat. The extent of tumoridentified was not as accurate as with the cortex exposed. However, thearea lying beneath the skull with tumor tissue was easily identified andlocalized, and continued to concentrate dye after several minutes.

After dye injection, the area of the tumor initially demonstrated a muchlarger signal than the normal brain of the contralateral hemisphere. Oneminute after dye injection, the dye had been cleared from the normalbrain and the only residual signal remained in tumor tissue and thesagittal/transverse sinuses.

FIG. 5A is a gray-scale image of the cranial surface of a rat. Thesagittal suture runs down the center of the image. Tumor cells had beeninjected into the left side some days earlier so that this animal haddeveloped a glioma on the left hemisphere of its brain. The righthemisphere was normal. Box 1 lies over the suspected region of braintumor, and box 2 lies over normal tissue. FIG. 5B is a difference image1 second after indocyanine green dye had been intravenously injectedinto the animal. The region containing tumor tissue becomes immediatelyvisible through the intact cranium. FIG. 5C shows that the dye can beseen to profuse through both normal and tumor tissue 5 seconds after dyeinjection. FIG. 5D shows that 1 minute after dye injection, the normaltissue has cleared the dye, but dye is still retained in the tumorregion. The concentration of dye in the center of this difference imageis dye circulating in the sagittal sinus.

The time course of optical changes imaged through the cranium from tenruns in four animals are shown in FIG. 6. The optical changes weredetermined by the average optical change in a box placed directly overthe tumor and over the normal hemisphere. The change in opticalproperties is a function of the concentration of dye in the tissue at aparticular time. The graph labeled “extracranial tumor” is a plot of thedynamics of the absorption changes within box 1 from FIG. 5A. The graphlabeled “extracranial: normal” is a plot of the dynamics of theabsorption change within box 2 from FIG. 5A. The peak optical changesfor the tumor imaged through the cranium were 13.1±3.9% which wassignificantly greater compared to those of normal brain of 7.8±2.3%(p<0.01). The plateau phase 60 seconds after dye injection was alsosignificantly greater in tumor tissue (40.5±9.6%) compared to normalbrain (3.1±0.7%) (p<0.01).

EXAMPLE 7

This example illustrates various methods for enhancing images obtainedfrom tumor tissue using multiple wavelength and/or laser illumination,and a method for extracting three-dimensional information using multiplewavelengths. We expose a region of cortex in an anesthetized rat, inwhich we have induced tumor growth. First, illuminating with white lightfrom a tungsten filament lamp, we acquire a first sequence of differenceimages prior to and following administration of a dye, such asindocyanine green or Evans blue, into the area of interest. Next, weacquire second and third difference image sequences, following theidentical procedure for the first sequence, except that in the secondsequence, the cortex is illuminated with 690 nm and in the thirdsequence with 510 nm light. The change in wavelengths is accomplished byplacing either a 690±10 nm cutoff filter or a 510±10 nm cutoff filterbetween the lightsource and the area of interest.

We compute the contrast-enhanced image by first ratioing a control 690nm image with a control 510 nm image. Second, we ratio a 690 nm imagefollowing dye administration with the corresponding 510 nm image. Wethen combine the ratio images to compute the percentage differenceimage. In this manner, the noise has been significantly reduced, hencethe signal/noise ratio has been significantly increased.

Next, we extract depth information from the multiple wavelength imagesthat we have acquired as follows. Longer wavelength light penetrates toa greater depth through the cortex than shorter wavelength light. Hence,the 690 nm image penetrates the cortex to x mm, and the 510 nm image toy mm where x<y. We subtract the 610 nm image from the 510 nm image,showing an “optical wedge” containing information from a depth of (x−y)mm to x mm within the cortical tissue. By using a series of other cutofffilters, we acquire a sequence of images containing information frommany different depths of the cortex. Thus, it is possible to acquirethree-dimensional information.

We claim:
 1. A method for detecting margins and dimensions of tumortissue in an area of interest, comprising: (a) illuminating the area ofinterest with an illumination source emitting electromagnetic radiation(emr) having at least one wavelength which interacts with a dye; (b)administering the dye to the area of interest; (c) detecting one or moreoptical properties of the area of interest subsequent to administrationof the dye and thereby acquiring a subsequent data set representing theone or more optical properties of the area of interest subsequent to theadministration of the dye; (d) comparing the subsequent data set with acontrol data set representing the one or more optical properties of thearea of interest prior to administration of the dye to produce acomparison data set; and (e) distinguishing tumor from non-tumor tissuein the area of interest based on differences in the one or more opticalproperties evidenced in the comparison data set, the differences in theone or more optical properties “representing” different dynamics of dyeperfusion in tumor and non-tumor tissue.
 2. A method according to claim1, wherein the dye is selected from the group consisting ofindocyanines, fluoresceins, hematoporphyrins, fluoresdamines andcombinations thereof.
 3. A method according to claim 1, wherein the areaof interest is located underneath at least one of intact skin and boneand the emr is in the infrared region.
 4. A method according to claim 1,step (c), wherein detecting is carried out with a CCD apparatus.
 5. Amethod according to claim 1, additionally comprising compensating formovement in the area of interest by aligning markers indicatingcorresponding spatial locations in the control and subsequent data setsto produce the comparison data set.
 6. A method according to claim 1,wherein the control data set is a control image, the subsequent data setis a subsequent image, and the comparison data set is a comparisonimage.
 7. A method according to claim 6, wherein the control andsubsequent images are obtained as analog video signals and the analogvideo signals are amplified and spread across a full dynamic range.
 8. Amethod according to claim 6, additionally comprising mapping differentpixel values comprising the comparison image to color values to enhancethe contrast of the comparison image.
 9. A method according to claim 1,wherein the optical property detected is selected from the groupconsisting of: reflection; refraction; diffraction; absorption;scattering; birefringence; refractive index; and Kerr effect.
 10. Amethod according to claim 1, wherein the comparison data set isdisplayed in a graphical format.
 11. A method according to claim 1,wherein the subsequent data set comprises a plurality of subsequent datapoints representing optical property values corresponding to specified,spatially resolved subsequent locations in the area of interest, thecontrol data set comprises a plurality of control data pointsrepresenting optical property values corresponding to specified,spatially resolved control locations in the area of interest, whereinthe subsequent locations and the control locations are at the samespatial locations in the area of interest.
 12. A method according toclaim 1, wherein the subsequent data set and the control data set eachinclude a plurality of data points that are spatially resolved withrespect to the area of interest, and the comparison data set comparescontrol and subsequent data points having the same spatial location inthe area of interest.
 13. A method of grading or characterizing tumortissue located in an area of interest, comprising: (a) illuminating thearea of interest with an illumination source emitting electromagneticradiation (emr) having at least one wavelength which interacts with adye; (b) administering the dye to the area of interest; (c) detectingone or more optical properties of the area of interest subsequent toadministration of the dye and thereby acquiring a subsequent data setrepresenting the one or more optical properties of the area of interestsubsequent to administration of the dye; (d) comparing the subsequentdata set with a control data set representing the one or more opticalproperties of the area of interest to produce a comparison data set; and(e) differentiating grades of tumors in the area of interest based ondifferences in the one or more optical properties evidenced in thecomparison data set, the differences in the one or more opticalproperties representing different dynamics of dye perfusion in differentgrades of tumor tissue.
 14. A method according to claim 13, wherein thedye is selected from the group consisting of indocyanines, fluoresceins,hematoporphyrins, fluoresdamines and combinations thereof.
 15. A methodaccording to claim 13, wherein the area of interest is locatedunderneath at least one of intact skin and bone and the emr is in theinfrared region.
 16. A method according to claim 13, step (c), whereindetecting is carried out with a CCD apparatus.
 17. A method according toclaim 13, additionally comprising compensating for movement in the areaof interest by aligning markers indicating corresponding spatiallocations in the control and subsequent data sets to produce thecomparison data set.
 18. A method according to claim 13, wherein thecontrol data set is a control image, the subsequent data set is asubsequent image, and the comparison data set is a comparison image. 19.A method for detecting the presence of tumor tissue in an area ofinterest suspected to contain tumor tissue comprising: (a) illuminatingthe area of interest with at least two different wavelengths ofelectromagnetic radiation (emr); (b) obtaining a sequence of controldata sets corresponding to the area of interest for each wavelength ofemr; (c) administering a dye to the area of interest; (d) obtaining asequence of subsequent data sets corresponding to the area of interestfor each wavelength of emr following administration of the dye; and (e)obtaining a series of comparison data sets for each wavelength of emr bysubtracting one of the control data set and the subsequent data set fromthe other of the control data set and the subsequent data set.
 20. Amethod according to claim 19, additionally comprising obtaining anenhanced comparison data set by ratioing a first comparison data set toa second comparison data set.
 21. A method according to any of claims 1,13, 11 or 19, wherein the optical detector is a video camera.
 22. Amethod according to any of claims 1, 13, 11 or 19, additionallycomprising amplifying portions of the control data set to enhance thecontrast of the comparison data set.
 23. A method according to claim 19,additionally comprising displaying the comparison data set in a visualimage format.
 24. A method according to claim 11, wherein each of thecontrol data points and the subsequent data points is detected using aCCD apparatus.
 25. A method according to claim 11, additionallycomprising acquiring a plurality of control data sets and a plurality ofsubsequent data sets, averaging the plurality of each of the controldata sets to produce an averaged control data set, and averaging theplurality of each of the subsequent data sets, and comparing theaveraged subsequent data set with the averaged control data set.
 26. Amethod according to claim 11 or 19, wherein the area of interest islocated underneath at least one of intact skin and bone, and theilluminating and detecting takes place through the at least one ofintact skin and bone.
 27. A method according to claim 11 or 19, whereinthe comparison data set is an image and processing provides an enhancedcontrast color image.
 28. A method according to claim 11, whereincomparing the subsequent data set with a control data set to distinguishtumor from non-tumor tissue in each of the spatially resolved locationsin the area of interest distinguishes between positive-going andnegative-going changes.
 29. A method according to any of claims 1, 13 or19, comprising illuminating the area of interest with uniform intensityemr.
 30. A method according to any of claims 1, 13 or 19, comprisingilluminating the area of interest with non-continuous illumination. 31.A method according to any of claims 1, 13 or 19, comprising illuminatingthe area of interest with an illumination source using at least one ofthe following: amplitude modulated; frequency modulated; and phasemodulated techniques.
 32. A method according to any of claims 1, 13, 11or 19, comprising producing the comparison data set in real-time.
 33. Amethod according to claim 11, wherein one or more spatially resolvedlocations in the area of interest is detected using at least one of thefollowing detectors: at least one photodiode; at least onephotomultiplier tube; at least one camera; at least one video camera;and at least one CCD camera.
 34. A method according to claim 11, whereinone or more spatially resolved locations in the area of interest is isilluminated using at least one of the following sources: atungsten-halogen lamp; a laser; a laser diode; and a light-emittingdiode.
 35. A method according to any of claims 1, 13, or 19, wherein atleast one blood characteristic is monitored simultaneously withdifferences in the dynamics of dye perfusion in tumor and non-tumortissue in the area of interest.
 36. A method according to any of claims1, 13, or 19, wherein the area of interest is illuminated using at leastone optical fiber operably connected to an emr source.
 37. A methodaccording to any of claims 1, 13, or 19, wherein the area of interest isdetected using at least one optical fiber operably connected to anoptical detector.
 38. A method according to any of claims 1, 13, 11 or38 wherein the area of interest is breast tissue.
 39. A method accordingto any of claims 1, 13, 11 or 19, wherein the dye is indocyanine green.40. A method according to any of claims 1, 13 or 19, wherein the dye isconjugated to a targeting molecule.